code: def test_computes_periodic_function(self):
      a = torch.tensor([4, 2, 8], dtype=torch.float).view(3, 1)
      b = torch.tensor([0, 2], dtype=torch.float).view(2, 1)
      lengthscale = 2
      period = 3
      kernel = PeriodicKernel().initialize(
          lengthscale=lengthscale, period_length=period
      )
      kernel.eval()
  
      actual = torch.zeros(3, 2)
      for i in range(3):
          for j in range(2):
              val = (
                  2
                  * torch.pow(torch.sin(math.pi * (a[i] - b[j]) / 3), 2)
                  / lengthscale
              )
              actual[i, j] = torch.exp(-val).item()
  
      res = kernel(a, b).to_dense()
      self.assertLess(torch.norm(res - actual), 1e-5)
  
file_path: gpytorch/test/kernels/test_periodic_kernel.py
imports: import math
  import unittest
  import torch
  from gpytorch.kernels import PeriodicKernel
  from gpytorch.priors import NormalPrior
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 3 for calling the TestPeriodicKernel obj's underlying member method code with example usage: obj.test_computes_periodic_function() without return types